Besides its obvious scientific uses, NumPy can also be used as an
efficient multi-dimensional container of generic data. Arbitrary
data types can be defined. This allows NumPy to seamlessly and
speedily integrate with a wide variety of databases.

NumPy is a successor for two earlier scientific Python libraries:
NumPy derives from the old Numeric code base and can be used
as a replacement for Numeric. It also adds the features introduced
by Numarray and can also be used to replace Numarray.

Numpy is a distributed, volunteer, open-source project. You can help
us make it better; if you believe something should be improved either
in functionality or in documentation, don’t hesitate to contact us — or
even better, contact us and participate in fixing the problem.